IF anyone had predicted the lotto numbers with Neural Nets or any method,
would they
1. Tell you how they did it.
2. Read this newsgroup from a beach front resort, while surrounded by the
most beautiful compliant bodies and the wonderous trappings of material
success that their ability could affort them.
3. Educate someone like yourself.
Breathe, breathe, think, breathe, repeat if necessary.
Klaus Breslauer
Conrad Thames <conrad...@yahoo.com> wrote in message
news:82cglt$ajv$1...@bgtnsc01.worldnet.att.net...
To hear bj flanagan tell it, this should be easy using HNeT.
Will Dwinnell
pred...@compuserve.com
>Network BlitzIs there anyone out there who has tried to use artificial
>neural network technology to predict a lottery outcome successfully? If so,
>what approach did you use?
>
You cannot predict any lottery outcome. You can use a neural network
to show that it can't be done. If you produce a neural network that is
trained to find relationships between historical lottery draws then it
will find some. If you then test it with different draws it will be
wrong in every case.
Steve
--
Steve Wolstenholme
Neural Network Applications for Windows
http://www.tropheus.demon.co.uk
..[predict a lottery outcome]...
>You cannot predict any lottery outcome. You can use a neural network
>to show that it can't be done. If you produce a neural network that is
>trained to find relationships between historical lottery draws then it
>will find some. If you then test it with different draws it will be
>wrong in every case.
>
It depends on your definition of prediction. I would interpret this
Question like this: whats the likelihood for every number to be drawn.
This is predictable. And you can find differences between the theo-
retical homogeneous likelihood and the real statistical likelihood.
But: the differences do not give you a chance to get more money back
than you pay for the lottery. The german Lotto "6 aus 49" gives only
50% back. So you must double your prediction. This looks a little bit
impossible. If you try to make money: work for the lotteries!
If you realy try to make make by gambling yous should use statistics
and think about the major occurenc of the numbers from 1 to 12 (month)
and 1 to 31 (day) and so on...
IOU / MfG
Uwe Borchert
Conrad Thames a écrit:
I think I finally >>got it<< !!!
HNet is clairvoyant !!
Paul
I was involved in an intense effort to show that such prediction is
not possible.... or show that it is. The lottery was the Italian
lottery. Historical record is over a 100 year period. 4 or 6 lottery
sites are involved (I can't remember which). Lottery rules changed 2
or 3 times during the 100 year period covered by the record. VERY
explicit and detailed description is available for all processes and
mechanisms used in the lottery. Details of known and documented cases
of "stacking the lottery" are recorded over the past 100 years.
Lottery methods have been perfected especially over the past 3 decades
or so that make cheating impossible or easily identified and
corrections made for the effects of cheating.
The method I used to perform this test is based on my commercial
software: back prop with a coupled simulating-annealing plus error
correction algorithm that simultaneously optimized network "energy"
and training error (which makes a "tight" fit with low errors... sort
of like constraining the second derivative of the "fitted function"
with a maximum tension algorithm). Brainstates were developed for many
scenarios, including time windowed data, non windowed data, prediction
of lotto results in each of the 4 or 6 lotto sites, prediction of the
ultimate lotto from raw data, prediction of ultimate lotto from the 4
or 6 lotto sites, etc.
Results showed an amazing and very frightening ability of my
commercial software product to match lotto results nearly 100% of the
time (for the valid portions of the data sets) regardless of how the
data was organized or segmented. Very small brainstates produced very
scary results.
Results also showed that once a brainstate was developed that matched
the data perfectly or almost perfectly, there was ABSOLUTELY NO
ABILITY OF THAT TRAINED BRAINSTATE TO PREDICT ANY EVENT IN THE FUTURE.
Conclusions: NNs of the type I used are able to encode ordered
structure and events almost perfectly for the system being
investigated. The encoding apparently utilized the large number of
effective-degrees-of-freedom contained in the brainstates as a matter
of the fitting method used (backprop with embedded annealing plus
optimization of network energy and error residuals).
Discussion: One would not think that there could be enough degrees of
freedom in a simple NN brainstate to encode random lotto results over
the past 100 years (minus some bogus data), but that is what MUST be
happening. No one knows how to estimate the number of degrees of
freedom in a back prop NN... but this study shows that (depending on
the system being studied) there can be an extremely large number of
effective-degrees-of-freedom encoded by simple structures. That there
was not one lotto result that was able to be predicted even as well as
"a throw of the dice" is proof that no predictive structure was
encoded by the NNs. They merely "grandmothered" the entire system....
even with all the protections against such "grandmothering" that were
utilized.
A separate study was undertaken to predict Texas lotto results several
years ago. The result of that study was that over about a 3 month
cycle a NN was able to "get better" at predicting lotto results. Then
things would fall apart again. My interpretation was that the
mechanical mechanisms used to perform the lotto were somehow involved,
and the continual monitoring and refurbishing of the devices (which
oddly enough seemed to coincide more or less with the "change of
states" detected by the ability/inability of a trained NN to predict
results) was based on sound statistical studies and theory so that the
system would remain as random as possible. However, this study also
demonstrated that there would be no way to predict the lottery.... and
that was back then. The game has been changed enough since then to
eliminate any ability to predict results (e.g., once a ball is
removed, another with the same numerical symbols is added so that
probability to select any number remains the same as a function of the
time during which the lottery is being performed).
These tests were NOT pursued because I thought they would be a
success. My intent was to test my system on random systems to make
certain there were not biases in the code. I made full disclosure of
this to the people for whom I performed the studies and made NO
representations that I thought the tests would provide what they
wanted. I have never, do not now, nor will I ever think that lotto
results can be predicted by anyone other than God. And He has made it
clear that He is not talking about that sort of stuff.
In some games of chance the situation is somewhat different. For example,
with roulette the odds are only slightly in the house's favour. So if you
can take advantage in any imbalance in the wheel, you might have a chance at
swinging the odds in your favour. (I am only looking at the example
theoretically. The number of observations one would have to use would be
enormous, rendering the exercise potentially intractable. However, in
theory, it might work.) Horse racing may also be another arena where there
is potential, since the odds are only marginally against the punter.
But the lottery? Forget about it. Buy tickets if you must but don't spend
any more time trying to increase the odds of a very poor bet.
Peter Davies
I believe the fundamental limitation in using Neural Nets to predict
financial markets is the assumption that enough of the information needed
for good predictions is contained in the price/value history, which it is
clearly not.
Phase one was developing a new methodology for general neural network
prediction, and luckily the contest where I first tried it out was to ..ta
da.. predict financial markets, which I won.
http://www.cas.american.edu/~medsker/ijcnn99/ijcnn99.html
As for lottery predictions, I spent about two weeks this summer playing with
the Canadian 6/49 data, astrological and geometrical positions of the
heavenly bodies, and regularly TRAINED nets that were GREAT at remembering
the winning patterns. However, they never did TEST worth a damn, and that
lead to a large study of the 'randomness' of correlations, the results of
which assist me in deciding which composite functions to keep out of the
billions of possibilities.
I did get one net to TEST fairly well on the Lotto, but that was due to a
logical error in the use of spline-fitting algorithms. Basically, I gave
the net an input peak at the future, which of course is flawed. I must
admit to having been quite excited for about 10 minutes, then I had to
figure out where I went wrong.
My main point was that, who would give away what was worth millions?
Best luck on the lotto, I'm playing with some sports information, to see if
I can successfully add the non-numeric data, and then beat the bookies. And
then the brokers.
Klaus Breslauer, UBC
Andrew Gray <ag...@infoscience.otago.ac.nz> wrote in message
news:uso1hn...@infoscience.otago.ac.nz...
> "Breslauer Family" <fam...@direct.ca> writes:
> > Please attempt to breathe and think at the same time.
> > IF anyone had predicted the lotto numbers with Neural Nets or any
method,
> > would they
> > 1. Tell you how they did it.
> > 2. Read this newsgroup from a beach front resort, while surrounded by
the
> > most beautiful compliant bodies and the wonderous trappings of material
> > success that their ability could affort them.
> > 3. Educate someone like yourself.
> >
> > Breathe, breathe, think, breathe, repeat if necessary.
> ^think, ^think,
> (I'd insert a few more `think's there)
>
> This obviously also goes for predicting financial markets.
>
> > Conrad Thames <conrad...@yahoo.com> wrote in message
> > news:82cglt$ajv$1...@bgtnsc01.worldnet.att.net...
>
> >> Network BlitzIs there anyone out there who has tried to use
> >> artificial neural network technology to predict a lottery outcome
> >> successfully? If so, what approach did you use?
>
> The best you could do, with any lottery prediction scheme (as I'm sure
> has been discussed in this group before, is this a FAQ yet?), is to
> predict which numbers and combinations of numbers people select and
> then select different numbers and combinations to maximise your payout
> (by minimising the number of winners you have to share with when your
> numbers do come up). You would probably be better sticking with
> classical probability for this where you could derive exact solutions
> (assuming stationarity).
>
> Cheers,
> Andrew
I find it absolutely astounding, amazing that people ask for solutions to
valuable problems be given to them. I guess learning how to search using a
decent engine like Altavista is just too hard. Maybe they could try +"free
money" +"easy street" -amway +"idiots' guide to making big money with no
effort"
Best of luck on neural stuff...
Klaus
Andrew Gray <ag...@infoscience.otago.ac.nz> wrote in message
news:ud7skl...@infoscience.otago.ac.nz...
> "Breslauer Family" <fam...@direct.ca> writes:
> > I wouldn't be too sure.
> > I am on phase 2 of a 3 part plan to seriously test the financial
> > markets prediction stuff.
>
> My point was that if anyone did `solve' any of the financial market
> prediction problems they would be unlikely to share their acquired
> knowledge. Ditto for any other money making schemes.
>
> <SNIP>
>
> > Andrew Gray <ag...@infoscience.otago.ac.nz> wrote in message
> > news:uso1hn...@infoscience.otago.ac.nz...
> >> "Breslauer Family" <fam...@direct.ca> writes:
> >>> Please attempt to breathe and think at the same time.
> >>> IF anyone had predicted the lotto numbers with Neural Nets or any
> >>> method, would they
> >>> 1. Tell you how they did it.
> >>> 2. Read this newsgroup from a beach front resort, while
> >>> surrounded by the most beautiful compliant bodies and the
> >>> wonderous trappings of material success that their ability could
> >>> affort them.
> >>> 3. Educate someone like yourself.
> >>>
> >>> Breathe, breathe, think, breathe, repeat if necessary.
> >> ^think, ^think,
> >> (I'd insert a few more `think's there)
> >>
> >> This obviously also goes for predicting financial markets.
>
> <SNIP>
>
> Cheers,
> Andrew
>
>
>
This obviously also goes for predicting financial markets.
> Conrad Thames <conrad...@yahoo.com> wrote in message
My point was that if anyone did `solve' any of the financial market
prediction problems they would be unlikely to share their acquired
knowledge. Ditto for any other money making schemes.
<SNIP>
> Andrew Gray <ag...@infoscience.otago.ac.nz> wrote in message
> news:uso1hn...@infoscience.otago.ac.nz...
>> "Breslauer Family" <fam...@direct.ca> writes:
>>> Please attempt to breathe and think at the same time.
>>> IF anyone had predicted the lotto numbers with Neural Nets or any
>>> method, would they
>>> 1. Tell you how they did it.
>>> 2. Read this newsgroup from a beach front resort, while
>>> surrounded by the most beautiful compliant bodies and the
>>> wonderous trappings of material success that their ability could
>>> affort them.
>>> 3. Educate someone like yourself.
>>>
>>> Breathe, breathe, think, breathe, repeat if necessary.
>> ^think, ^think,
>> (I'd insert a few more `think's there)
>>
>> This obviously also goes for predicting financial markets.
<SNIP>
Cheers,
Andrew
The original Q was about lotto, not predicting the monetary activity
of socio-ec systems.
>
>I believe the fundamental limitation in using Neural Nets to predict
>financial markets is the assumption that enough of the information needed
>for good predictions is contained in the price/value history, which it is
>clearly not....
Predicting a system with erroneous formalism will produce prediction
errors. If the formalism is improperly parameterized, then even the
best formalism will produce prediction errors.
Regarding NNs vs linear methods used for predicting financial systems,
see:
".... In short, there is little agreement about the existence of chaos
or even of non-linearity in economic data, and some economists
continue to insist that linearity remains a good assumption for all
economic time series, despite the fact that economic theory provides
little support for the assumption of linearity. This paper explores
the reasons for these empirical difficulties. ...."
This is from "A SINGLE-BLIND CONTROLLED COMPETITION AMONG TESTS FOR
NON-LINEARITY AND CHAOS" which can be obtained here:
> Is there anyone out there who has tried
> to use artificial neural network technology
> to predict a lottery outcome successfully?
> If so, what approach did you use?
Yes. Many people have tried many different approaches.
But the lottery is designed or at least should be designed
to be unpredictable and there are a lot of professional people
who run tests to make sure that it isn't rigged
or that some other unintentional systematic "bias"
isn't introduced into the system. But I don't know
whether anyone uses ANNs to do any of this work.
It is better to turn your attention to financial markets
where there are small built-in biases that you may be able
to detect with an artificial neural network.
There are people all over the world who do this
but they guard their secrets carefully
mostly because they don't want their competition
to know how bad or good their tools really are.
..[...]...
>
>As for lottery predictions, I spent about two weeks this summer playing with
>the Canadian 6/49 data, astrological and geometrical positions of the
>heavenly bodies, and regularly TRAINED nets that were GREAT at remembering
>the winning patterns. However, they never did TEST worth a damn, and that
>lead to a large study of the 'randomness' of correlations, the results of
>which assist me in deciding which composite functions to keep out of the
>billions of possibilities.
>
I would prefer another way of thinking. Every ball has mechanical
properties. This mechanical properties would influence the statistics.
Next would be to describe the likelihood of the number in relation to
the old drawings results. You need a lot of data input and you can
throw it away i the balls are changed. And dont forget to predict
which numbers and combinations of numbers people select. So the result
should be something like: a few combination with high likelihood and
with less often selected numbers.
ByByte...
Uwe Borchert
You can e.g. use MLP with backprob learning using the history to
learn the network. You must have enough history data available.
In practice, it is learning noise and you will get quite random
outputs just like using some random number generator. Not a better
approach than any other.
Juha K.
Sent via Deja.com http://www.deja.com/
Before you buy.
Andrew Gray wrote in message ...
>"Breslauer Family" <fam...@direct.ca> writes:
>> I wouldn't be too sure.
>> I am on phase 2 of a 3 part plan to seriously test the financial
>> markets prediction stuff.
>
ju...@my-deja.com responded:
"You can e.g. use MLP with backprob learning using the history to learn
the network. You must have enough history data available. In practice,
it is learning noise and you will get quite random outputs just like
using some random number generator. Not a better
approach than any other."
You will not get "random" results. Assuming that one overfit the data,
you will get a very strange function which is anchored at random points,
but which will move more or less smoothly between them. Assuming that
one does not overfit the data, the output will approach the
probabilities of the numbers being drawn over the long run. Significant
differences from the analytical probabilities will be difficult to
detect using this method.
Will Dwinnell
pred...@compuserve.com
If the means tend to group together within the range of normalizations
(ie, if all normalized means group around the value 0.5 or 0.2 or 0.8
or whatever), and the variances are large compared to the spread of
the means, then "safe", non-overfit brainstates will probably produce
uninteresting, fairly "dead", inactive results, eh? The best fit to
"noise" is a fairly straight line.
What do you think?
-Jeff
We offer BioComp Profit, a successful financial markets timing software
tool. It's available, in demo mode, from our website at:
>My point was that if anyone did `solve' any of the financial market
>prediction problems they would be unlikely to share their acquired
>knowledge. Ditto for any other money making schemes.
We sell BioComp Profit because it works. We're a software company. If we
create software that works, we sell it and customers buy it <wink>.
Carl Cook
BioComp Systems, Inc.